Previous Course Code(s): ENVR 6040G

The study of atmospheric motions is essential for a better understanding of the relevant meteorological phenomena. This course introduces the conservation laws for primitive equations and classical concepts in fluid dynamics, which will allow students to gain physical insight into the fundamental nature of atmospheric motions. This course is suitable for students who require the foundation of fluid dynamics for advanced study in meteorology, oceanography, atmospheric and climate sciences.

On successful completion of the course, students will be able to:

• Apply the basic concepts of fluid dynamics and key variables describing the structure and motion of atmosphere.
• Formulate the primitive equations and perform their simplifications.
• Define circulation and vorticity, and their relationship.
• Describe dynamical structure of the flow in the planetary boundary layer.
• Describe the quasi-geostrophic theory to depict and explain the mid-latitude synoptic-scale motions.
• Interpret the observed characteristics of large-scale atmospheric motions with fundamental principles.

Co-list with: CHEM 5410

Exclusion(s): CHEM 5410

Background: Basic knowledge of physical chemistry

A fundamental introduction to the physical and chemical processes determining the composition of the atmosphere and its implications for climate, ecosystems, and human welfare. Atmospheric transport and transformation. Stratospheric ozone. Oxidizing power of the atmosphere. Regional air pollution: aerosols, smog, and acid rain. Nitrogen, oxygen, carbon, sulfur geochemical cycles. Climate and the greenhouse effect.

On successful completion of the course, students will be able to:

• Apply the fundamental concepts to describe the physical and chemical processes governing air pollution.
• Identify important chemical reactions and processes in the stratosphere and troposphere.
• Understand the formation mechanism and destruction processes of various pollutants in the air.
• Assess the potential impacts of various atmospheric chemical processes on environment, climate and human health.
• Use investigative skills, critical thinking and ability to evaluate atmospheric chemistry-related information and data.

Historical and health impact studies related to air pollution. Atmospheric stability and its impact on the transport and dispersion of pollutants. Sources of major air pollutants. Comparison of urban, industrial and transport related air pollution issues, using Hong Kong and Pearl River Delta as examples. Control of stationary and mobile emission sources. Air quality management - framework, policy tools and comparison of different approaches.

This course prepares graduate students for the development of interdisciplinary research on environmental science, policy and management through a detailed investigation of climate change issues. Based on a review of the scientific research and models that have been developed through international cooperation, students will discuss relevant approaches of atmospheric and oceanographic science and the likely consequences in terms of climate change. In addition, the various technologies of mitigation and adaptation will be surveyed, leading to a discussion of appropriate policies for managing climate change at the global or national level.

On successful completion of the course, students will be able to:

• Explain the critical physical processes responsible for global warming and its impact.
• Summarize essential components of global climate models and analyze climate data set.
• Identify key stakeholders in climate discussions and policymaking and explain their roles.
• Evaluate the difficulties and opportunities of some technology options for climate adaptation and mitigation.
• Assess the strategy and progress in climate risk management by some countries through literature review and data analysis.

Background: Fundamental knowledge of the statistic concepts and experience in using at least one data analysis tool such as excel, python or Matlaby

This course is designed for students at the start of their postgraduate studies. The course will provide students with knowledge in understanding and using statistical methods in environmental science and applications. Probability distributions, parametric tests of significance against non-parametric tests, Monte Carlo methods, Principal Component Analysis, etc. will be taught in the course facilitated by extensive use of real world problems as example.

On successful completion of the course, students will be able to:

• Explain the concepts of basic statistical methods.
• Use probability distributions, parametric tests, non-parametric tests and Monte Carlo methods to analyze environmental database and solve environmental problems creatively.
• Use Principal Component Analysis, and correlation methods to analyze environmental datasets and discover the linkage between the data results and with environmental problems.
• Solve the real world environmental problems using statistical tools independently and creatively.

Exclusion(s): EVSM 5240

This course will cover a broad spectrum of concepts and practices in Geographical Information System (GIS). It starts with the fundamental concepts and elements in geographic science and technology. Spatial data modeling and integration methods will then be discussed followed by various geospatial analysis approaches for both vector and raster data. Cartographic principles, spatial relationships, projection and coordinate systems will be discussed in-depth. During the course, students will be introduced to contemporary GIS software and apply GIS technology support local and regional environmental planning and management.

On successful completion of the course, students will be able to:

• Manage spatial data, including images from satellites and field data.
• Interpret spatial model data such as wind and temperature in Hong Kong.
• Analyze situations to incorporate environmental considerations into socioeconomic development.
• Formulate solutions to environmental problems by integrating and applying geospatial technologies.
• Apply GIS theory to effective resource management, environmental policy formation and decision making.

Previous Course Code(s): ENVR 6040J

Background: Some engineering knowledge will be a plus while not a specific requirement.

The course is intended to link the interaction between the human and natural environment, focusing on how the anthropogenic activities have altered the natural environment and provide an overview on the emerging science and technology of sustainability. The course will identify the impacts associated with resource consumption and environmental pollution, and present the quantitative tools necessary for assessing environmental impacts and design for sustainability. At the end of the course, the students should be cognizant of the concept of sustainability, the metrics of sustainability and be able to use the principles of sustainable engineering in their respective field of practice.

On successful completion of the course, students will be able to:

• Describe and explain social, environmental, and ecological indicators of Sustainability.
• Identify grand challenges for sustainability and discuss emerging solutions for these challenges.
• Define and explain the principles of sustainable engineering and make links to their respective field of practice.
• Apply a life-cycle thinking in design for environment and conduct life cycle analysis to assess the environmental impacts of different products, processes and systems.
• Work effectively in a team and interpret the project‘s contribution to sustainability improvement.

Background: Fundamental knowledge of (geophysical) fluid dynamics is recommended.

This course covers the dynamics of the atmosphere and ocean and the coupled dynamics, which govern our weather and climate. The course will introduce the essential features of the atmosphere and ocean circulation, as well as theories about instabilities in geophysical fluids. Knowledge and skills for running weather and climate models and analyzing data are also practiced in the course.

On successful completion of the course, students will be able to:

• Describe basic structures of the atmospheric and oceanic circulation.
• Explain known mechanisms governing the variability of the climate.
• Conduct further research related to climate variability.
• Present their research/practice results to experts and general audience.

This course introduces postgraduate students to critical sustainability challenges and the state-of-the-art sustainable development practices. The course will cover the up-to-date research in understanding the emergence of sustainability challenges and solution development. It will combine lectures and in-class discussions to provide students with the opportunity to think outside their ongoing research framework and enhance their transdisciplinary research capabilities of delivering useful knowledge and methods that contribute to sustainable development.

On successful completion of the course, students will be able to:

• Recognize the importance of sustainable development and the necessity of interdisciplinary collaboration in the delivery of sustainable development instruction and assessment.
• Understand and explain the causes of critical sustainability challenges.
• Design and integrate multi-disciplinary knowledge to define a research framework for solving a particular sustainable development issue.
• Experience problem solving and collaboration in studying solution development.
• Connect and expand their current research domain to the area of sustainable development in pursuit of future academic careers.

Satellite remote sensing technique measures geophysical parameters from the electromagnetic energy emitted or reflected from the earth, and can be used to estimate earth surface characteristics, atmospheric compositions and profiles, and meteorological processes. This course provides a brief overview of the fundamental essentials to understand the remote sensing process, satellite data products, and their applications in atmosphere, land, and ocean.

On successful completion of the course, students will be able to:

• Identify and describe the algorithm and process used by satellite remote sensing to measure the physical properties of distant objects.
• Compare and contrast the most common sensors and techniques for satellite remote sensing.
• Explain basic electromagnetic concepts and applications to optical sensors.
• Define and exemplify the principles of applications in atmosphere, land, and ocean.
• Access satellite remote sensing products from online data archives.
• Apply data products for spatial and temporal variation analysis on parameters, compositions, and profiles of atmosphere, land, and ocean.

In this course, the students will gain a deeper understanding of the weather and climate systems that affect Hong Kong and the Asia/Pacific sector, the basic physical principles governing the atmospheric motion, and the formation mechanism of severe air pollution; and be able to use online tools to assess the cause of severe air pollution episodes in Hong Kong and mainland China.

On successful completion of the course, students will be able to:

• Explain how the weather and climatic systems affect Hong Kong and their associations with air pollution.
• Illustrate the basic physical principles and dynamics governing the atmospheric motion and circulation.
• Correlate the atmospheric thermodynamics and dynamics and their impacts to pollutant dispersion.
• Account for the causes of severe air pollution episodes, and in particular the interaction between weather, climate, and air pollution.
• Integrate the knowledge and utilize available web resources to explain the formation, maintenance, and dissipation of air pollution episodes in Hong Kong and mainland China.

Offerings are announced each term, if deemed necessary, to cover emerging topics in environmental science not covered in the present curriculum.

On successful completion of the course, students will be able to:

• Identify the latest development in the technologies or management strategies on the topic concerned.
• Integrate with the status quo knowledge/practices on the topic/subject.
• Project the near-future trend of development concerned.
• Anticipate the research/business/in-field opportunities on the topic/subject.

Atmospheric aerosols, also known as, airborne particulate matter, are important air pollutants affecting our health, visibility, and global climate change. This course aims to provide a survey of the physical and chemical properties, the source identification, the atmospheric transformation, the sampling of atmospheric aerosols, and the determination of their chemical compositions.

On successful completion of the course, students will be able to:

• Evaluate the air pollution problem, in particular that in Hong Kong and PRD, and the main contributing factors.
• Explain and use the basic concepts and terminology in atmospheric aerosols and particulate matter for communication and discussion.
• Identify the common aerosol parameters and atmospheric processes governing the changes of atmospheric aerosols.
• Apply the concepts and knowledge to analyze aerosol related air pollution issues.
• Work in a team to analyze and comment on an aerosols-related air pollution issue, like those reported in scientific papers, and present and communicate the findings to a group of audience.

Previous Course Code(s): EVSM 607, ENVR 607, AMCE 607

Exclusion(s): ENVS 5116

Introduction to environmental impact assessment (EIA) and the EIA process in Hong Kong. The components of an EIA report including air, noise, water, waste management, environmental risk, ecological impact, and socio-economic impact assessments will be analyzed. Environmental law, environmental management and the importance of public participation will also be discussed. Case studies from Hong Kong will be used and comparison with EIA in Mainland China will be made.

On successful completion of the course, students will be able to:

• Critically examine a broad range of environmental impacts in the EIA processes.
• Identify the complex interactions among the various key components in the assessment processes.
• Develop analytical and presentation skills to locate and evaluate the interactive dynamics between environment and scientific principles.

Previous Course Code(s): MATH 531

Numerical solution of differential equations, finite difference method, finite element methods, spectral methods and boundary integral methods. Basic theory of convergence, stability and error estimates.

On successful completion of the course, students will be able to:

• Recognize and use appropriately numerical techniques in computation.
• Develop numerical scheme to discretize partial differential equations.
• Apply numerical analysis to examine the consistency, stability and convergence of the numerical methods.
• Apply appropriate numerical schemes to solve real and hypothetical problems.

Previous Course Code(s): MATH 535

Derivation of the Navier-Strokes equations; the Euler equations; Lagriangian vs. Eulerian methods of description; nonlinear hyperbolic conservation laws; characteristics and Riemann invariants; classification of discontinuity; weak solutions and entropy condition; Riemann problem; CFL condition; Godunov method; artificial dissipation; TVD methods; and random choice method.

On successful completion of the course, students will be able to:

• Understand the characteristics in linear and nonlinear scalar equations, the concept of entropy, and the condition for the formation of discontinuous shock. Solve the Riemann problem for the nonlinear scalar equation with concave and convex flux functions. Develop numerical scheme to solve the Burgers' equation and traffic flow equation.
• Identify the characteristic variables for the linear hyperbolic system. Construct the analytical solution of the Riemann problem. Develop numerical scheme to solve the linear system.
• Obtain the characteristic variables for the nonlinear 2x2 system, such as the shallow water equations. Construct the analytical similarity solution for the Riemann problem and apply it to the wave interactions.
• Derive the gas dynamic Euler equations. Present the Euler equations in terms of conservative, characteristic and primitive variables. Construct the Riemann solution for the Euler equations. Identify the interaction among different kinds of waves.
• Develop numerical scheme for the Euler equations. Understand approximate Riemann solvers. Construct reliable numerical schemes beyond the inviscid Euler equations.

Previous Course Code(s): MATH 551

Modeling and analytical solution methods of nonlinear partial differential equations (PDEs). Topics include: derivation of conservation laws and constitutive equations, well-posedness, traveling wave solutions, method of characteristics, shocks and rarefaction solutions, weak solutions to hyperbolic equations, hyperbolic Systems, linear stability analysis, weakly nonlinear approximation, similarity methods, calculus of variations.

On successful completion of the course, students will be able to:

• Demonstrate abilities to describe problems in science and engineering by partial differential equation models.
• Apply analytical solution methods to solve nonlinear partial differential equations.
• Apply approximation methods to solve nonlinear partial differential equations.
• Demonstrate abilities to interpret the solutions of partial differential equation models for problems in science and engineering.

Previous Course Code(s): MATH 546

Basic idea of time series analysis in both the time and frequency domains. Topics include: autocorrelation, partial ACF, Box and Jerkins ARIMA modeling, spectrum and periodogram, order selection, diagnostic and forecasting. Real life examples will be used throughout the course.

On successful completion of the course, students will be able to:

• Introduce some basic concepts in time series such as auto-covariance, stationarity and ergodicity.
• Introduce time series models, such as AR models, ARMA models, threshold models, GARCH models, and study their properties.
• Study the theory of estimation and testing statistics of time series models.
• Study the diagnostic tools for identifying various models in practice.
• Introduce for possible applications such as option theory and risk management.

Prerequisite(s): MECH 2310

Exclusion(s): IBTM 5430, JEVE 5350

Indoor air pollutants in buildings and their transport dynamics with respect to building ventilation systems. Design methodology in handling indoor air quality in buildings and enclosed spaces. Building environmental assessment method.

Previous Course Code(s): MECH 521

Exclusion(s): AESF 5210, MESF 5210

Background: MECH 2210

Tensor notation, derivation of Navier-Stokes equations, vorticity transport, viscous flow, flow separation, boundary layer, flow instability, turbulent boundary layer, stratified flow, rotating flow.

On successful completion of the course, students will be able to:

• Be familiar with fundamental and advanced concepts in fluid mechanics.
• Theoretically analysze some practical fluid mechanics problems.
• Explain certain complex flow phenomena.

Previous Course Code(s): PHYS 511

Review of vector analysis; complex variable theory, Cauchy-Rieman conditions, complex Taylor and Laurent series, Cauchy integral formula and residue techniques, conformal mapping; Fourier series; Fourier and Laplace transforms; ordinary differential equations, Bessel functions; partial differential equations, wave and diffusion equations, Laplace, Helmholtz and Poisson's equations, transform techniques, Green's functions; integral equations, Fredholm equations, kernals; Rieman sheets, method of steepest descent; tensors, contravariant and covariant representations; group theory, matrix representations.

On successful completion of the course, students will be able to:

• Apply Cauchy integral formula and residue techniques.
• Understand calculus of variations.
• Solve ordinary differential equations.
• Understand common types of partial differential equations.
• Apply Green function and Fourier transform in solving differential equations.
• Apply conformal maps to solve differential equations.

The course aims to equip all full-time research postgraduate (RPg) students with basic teaching skills before assuming teaching assistant duties for the department. Good teaching skills can be acquired through learning and practice. This 10-hour mandatory training course provides all graduate teaching assistants (GTA) with the necessary theoretical knowledge with practical opportunities to apply and build up their knowledge, skills and confidence in taking up their teaching duties. At the end of the course, GTAs should be able to (1) facilitate teaching in tutorials and laboratory settings; (2) provide meaningful feedback to their students; and (3) design an active learning environment to engage their students. Graded PP, P or F.

On successful completion of the course, students will be able to:

• Identify fundamental theories and good practices in teaching and learning.
• Design appropriate active learning activities to engage students.
• Apply constructive alignment in designing a learning sequence.
• Demonstrate teaching and facilitation skills in different teaching settings.
• Formulate constructive feedback to assist students as they progress in their learning.